Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/mrtblount/spec-to-ship/specifiernpx skills add mrtblount/Spec-to-Ship --skill specifiergit clone --depth 1 https://github.com/mrtblount/Spec-to-ShipWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/mrtblount/spec-to-ship/specifier)<a href="https://agentmods.dev/skills/mrtblount/spec-to-ship/specifier"><img src="https://agentmods.dev/badge/skills/mrtblount/spec-to-ship/specifier.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00044 | $0.01641 |
| Opus 5 | $0.00022 | $0.00821 |
| Sonnet 5 | $0.00009 | $0.00328 |
| Haiku 4.5 | $0.00004 | $0.00164 |
Grade A, and why
specifier scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 5d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 193 lines — stays where its author put it; the contents beside it link to each section on GitHub.
The output is not for humans to read casually — it's a machine-parseable contract that defines exactly what "done" looks like.
Key insight from SDD methodology: Specs must be structured for machine comprehension, not just human readability. Use hierarchical Markdown, explicit invariants, and testable acceptance criteria.
IF user's description is vague or high-level:
ASK targeted questions (MAX 5 per round — don't overwhelm):
- "Who is the primary user? What's their situation when they use this?"
- "What's the ONE thing this must do well to be useful?"
- "What's explicitly out of scope for v1?"
- "Are there hard constraints? (platform, budget, compliance, timeline)"
- "Any existing products you like or want to differentiate from?"
AWAIT answers before proceeding
ELIF user's description is detailed:
SUMMARIZE understanding back to user
ASK: "Did I get that right? Anything I'm missing?"
AWAIT confirmation
Happy Path (the standard flow):
1. User arrives at [entry point]
2. User performs [action]
3. System responds with [response]
4. User sees [outcome]
5. ...continue until journey completes
Edge Cases (boundary conditions):
- Empty states (no data yet, first-time user)
- Maximum limits (too many items, too large file, rate limits)
- Concurrent access (two users editing same thing)
- Partial completion (user abandons halfway, network drops)
- Invalid input (wrong format, out of range, special characters)
Error States (what can go wrong):
- Network failures
- Authentication expiration
- Data validation failures
- External service outages
- Permission denied scenarios
For each error state, define: what the user sees, what the system does, how recovery works.
Present user journeys to user for validation before continuing.
Categories:
- Business Logic: Rules about data and operations (e.g., "order total = sum of line items")
- Data Integrity: Rules about data state (e.g., "email must be unique per account")
- Security: Rules about access and protection (e.g., "API keys never in client code")
- UX: Rules about user experience (e.g., "every destructive action requires confirmation")
- Performance: Rules about speed (e.g., "search results return within 500ms")
Format each invariant as:
INV-{NNN}: {rule statement} — {why this matters}
These must be testable. If you can't write a test for it, it's not specific enough.
In Scope (v1): List every feature/capability that WILL be built.
- Be specific: "User authentication via email/password" not "auth"
- Include data requirements: "Store user profile with name, email, avatar"
Explicitly Out of Scope: List things that might seem related but are NOT being built.
- For each, briefly state why (deferred to v2, not needed, too complex for now)
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 5d ago First seen · 193 lines · 44 tokens per session scan A 81bf41ff8b6f
specifier is a skill published in the GitHub repository mrtblount/Spec-to-Ship (2 stars, last pushed 1mo ago), licensed MIT. It adds 44 tokens to every session and 1,641 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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